CN116934397A - Content promotion method, content promotion device, computer equipment, storage medium and product - Google Patents

Content promotion method, content promotion device, computer equipment, storage medium and product Download PDF

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CN116934397A
CN116934397A CN202210365056.1A CN202210365056A CN116934397A CN 116934397 A CN116934397 A CN 116934397A CN 202210365056 A CN202210365056 A CN 202210365056A CN 116934397 A CN116934397 A CN 116934397A
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石志林
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Tencent Technology Shenzhen Co Ltd
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Tencent Technology Shenzhen Co Ltd
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    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
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    • G06Q30/0254—Targeted advertisements based on statistics
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    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0241—Advertisements
    • G06Q30/0242—Determining effectiveness of advertisements
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0241—Advertisements
    • G06Q30/0273—Determination of fees for advertising

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Abstract

The embodiment of the application discloses a content promotion method, a content promotion device, computer equipment, a storage medium and a product, wherein content promotion frequency of current promotion time and promotion success rate of content to be promoted are predicted according to historical promotion data; calculating bidding probabilities of contents to be promoted participating in content promotion bidding at the current promotion time according to historical promotion data, content promotion frequency and promotion success rate; if the bidding probability meets the preset condition, calculating the current bid based on the content promotion budget and promotion consumption of the content to be promoted; and at the current promotion time, content promotion bidding is carried out on the content to be promoted by using the current bid, and the content to be promoted comprises advertisements, multimedia content and the like. The scheme controls whether the content to be promoted participates in bidding through the bidding probability, adjusts the bidding of the content to be promoted, ensures that the promoting budget of the content to be promoted can be uniformly consumed, can be continuously exposed, and improves the promoting effect of the content to be promoted.

Description

Content promotion method, content promotion device, computer equipment, storage medium and product
Technical Field
The application relates to the technical field of communication, in particular to a content promotion method, a content promotion device, computer equipment, a storage medium and a product, wherein the storage medium is a computer readable storage medium, and the product is a computer program product.
Background
With the development of internet technology, the promotion of content through a network is a common promotion mode, the promotion budget consumption is mainly controlled through a bid-controlling mode (the higher the bid is, the higher the probability of success of bidding) at present, and the adjustable range of the bid is very small when the content is promoted due to the limitation of preset bid, and the modifiable range of the bid is also relatively small when the content is promoted for the promotion content close to the depleted budget and the limitation of residual budget, so that the uniform consumption of the budget is difficult to achieve through the bid mode, insufficient exposure in the promotion time is caused, and the promotion effect is poor.
Disclosure of Invention
The embodiment of the application provides a content promotion method, a content promotion device, computer equipment, a storage medium and a content promotion product, which can enable promotion budget of content to be promoted to be uniformly consumed, enable the content to be promoted to be continuously exposed and improve promotion effect of the content to be promoted.
The content promotion method provided by the embodiment of the application comprises the following steps:
predicting content promotion frequency of current promotion time according to historical promotion data, and promoting success rate of content to be promoted in the current promotion time;
calculating bidding probabilities of the content to be promoted participating in content promotion bidding at the current promotion time according to the historical promotion data, the content promotion frequency and the promotion success rate;
if the bid probability meets the preset condition, calculating a current bid based on the popularization budget and the residual popularization budget of the content to be promoted;
and at the current promotion time, carrying out content promotion bidding on the content to be promoted by the current bid.
Correspondingly, the embodiment of the application also provides a content promotion device, which comprises:
the prediction unit is used for predicting content promotion frequency of the current promotion time and promotion success rate of the content to be promoted at the current promotion time according to the historical promotion data;
the first calculating unit is used for calculating bidding probabilities of the content to be promoted participating in content promotion bidding at the current promotion time according to the historical promotion data, the content promotion frequency and the promotion success rate;
The second calculating unit is used for calculating the current bid based on the promotion budget and the residual promotion budget of the content to be promoted if the bid probability meets the preset condition;
and the bidding unit is used for bidding the content to be promoted by the current bid at the current promotion time.
In an embodiment, the first computing unit includes:
the probability calculation subunit is used for calculating the initial bidding probability of the content to be promoted participating in content promotion bidding at the current promotion time according to the historical promotion data, the content promotion frequency and the promotion success rate;
the range determining subunit is used for determining the popularization consumption range of the content to be promoted in the current popularization time according to a preset dynamic adjustment strategy;
and the probability adjustment subunit is used for adjusting the initial bidding probability based on the popularization consumption range to obtain the bidding probability, and the bidding probability enables the conversion cost of the content to be promoted to meet a preset condition.
In an embodiment, the range determining subunit comprises:
the first range determining module is used for calculating a first consumption range of the content to be promoted in the current promotion time according to the total promotion budget of the content to be promoted and a first preset threshold value;
The second range determining module is used for calculating a second consumption range of the content to be promoted in the current promotion time according to the current promotion budget and a second preset threshold value;
the third range determining module is used for calculating a third consumption range of the content to be promoted in the current promotion time according to thousands of times of display inflow data of the content to be promoted and preset thousands of people cost;
and the promotion consumption range determining module is used for determining the promotion consumption range based on the first consumption range, the second consumption range and the third consumption range.
In an embodiment, the historical popularization data includes a historical bid probability, and the first computing unit includes:
the consumption calculation subunit is used for acquiring average popularization consumption of the content to be promoted in the current popularization time;
a probability ratio subunit, configured to calculate a probability ratio between a current promotion time and the historical bid probability based on the historical promotion data, the average promotion consumption, the promotion success rate, and the content promotion frequency;
and the probability calculating subunit is used for calculating the initial bidding probability of the content to be promoted participating in content promotion bidding at the current promotion time based on the probability ratio and the historical bidding probability.
In an embodiment, the second computing unit includes:
the acquisition subunit is used for acquiring the initial bid of the content to be promoted at the current promotion time;
the parameter calculation subunit is used for calculating bid adjustment parameters of the content to be promoted according to the content promotion budget and promotion consumption of the content to be promoted;
and the bid adjusting subunit is used for adjusting the initial bid of the content to be promoted at the current moment based on the bid adjusting parameter to obtain the current bid.
In an embodiment, the historical promotion data includes promotion data of a plurality of historical promotion times, and the prediction unit includes:
the curve fitting subunit is used for performing curve fitting according to the popularization data of a plurality of historical popularization times in the historical popularization data to obtain a popularization frequency fitting curve and a success rate curve;
the content promotion frequency prediction subunit is used for predicting the content promotion frequency of the content to be promoted at the current promotion time based on the promotion frequency fitting curve;
and the promotion success rate prediction subunit is used for predicting the promotion success rate of the content to be promoted at the current promotion time based on the success rate curve.
In an embodiment, the content promotion device further includes:
the bidding result determining unit is used for determining that the content to be promoted is successful based on the current bidding price if the current bidding price meets a preset bidding price condition;
and the content sending unit is used for sending the content to be promoted to the promotion client so that the promotion client displays the content to be promoted.
Correspondingly, the embodiment of the application also provides computer equipment, which comprises a memory and a processor; the memory stores a computer program, and the processor is configured to run the computer program in the memory, so as to execute any content promotion method provided by the embodiment of the present application.
Accordingly, the embodiment of the present application also provides a computer readable storage medium, where the computer readable storage medium is used to store a computer program, where the computer program is loaded by a processor to execute any one of the content promotion methods provided by the embodiment of the present application.
Correspondingly, the embodiment of the application also provides a computer program product, comprising a computer program, wherein the computer program realizes any content promotion method provided by the embodiment of the application when being executed by a processor.
According to the embodiment of the application, the content promotion frequency of the current promotion time and the promotion success rate of the content to be promoted in the current promotion time are predicted according to the historical promotion data; calculating bidding probabilities of contents to be promoted participating in content promotion bidding at the current promotion time according to historical promotion data, content promotion frequency and promotion success rate; if the bidding probability meets the preset condition, calculating the current bid based on the content promotion budget and promotion consumption of the content to be promoted; and at the current popularization time, carrying out content popularization bidding on the content to be promoted by using the current bid.
According to the scheme, whether the content to be promoted participates in bidding is determined through predicting the bidding probability of the content to be promoted, so that quick consumption of the promotion budget of the content to be promoted is avoided, the bidding is adjusted through the content promotion budget and the promotion consumption calculation of the content to be promoted, the probability that the content to be promoted can bid successfully can be improved, whether the content to be promoted participates in bidding is controlled through the bidding probability, the promotion budget of the content to be promoted can be consumed is guaranteed through adjusting the bidding of the content to be promoted, the content to be promoted can be continuously exposed, and the promotion effect of the content to be promoted is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a scene diagram of a content promotion method provided by an embodiment of the present application;
FIG. 2 is a flow chart of a content promotion method provided by an embodiment of the present application;
FIG. 3 is another flow chart of a content promotion method provided by an embodiment of the present application;
fig. 4 is a schematic diagram of a content promotion device according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of a computer device according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
The embodiment of the application provides a content promotion method, a content promotion device, computer equipment and a computer readable storage medium. The content promotion device can be integrated in computer equipment, and the computer equipment can be a server, a terminal and other equipment.
The terminal can comprise a mobile phone, a wearable intelligent device, a tablet computer, a notebook computer, a personal computer (PC, personal Computer), an intelligent voice interaction device, an intelligent household appliance, a vehicle-mounted terminal, a vehicle-mounted computer and the like.
The server may be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, or a cloud server providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDNs, basic cloud computing services such as big data and artificial intelligent platforms.
For example, as shown in fig. 1, the computer device predicts the content promotion frequency of the current promotion time and the promotion success rate of the content to be promoted at the current promotion time according to the historical promotion data; calculating bidding probabilities of contents to be promoted participating in content promotion bidding at the current promotion time according to historical promotion data, content promotion frequency and promotion success rate; if the bidding probability meets the preset condition, calculating the current bid based on the content promotion budget and promotion consumption of the content to be promoted; and at the current popularization time, carrying out content popularization bidding on the content to be promoted by using the current bid.
According to the scheme, whether the content to be promoted participates in bidding is determined through predicting the bidding probability of the content to be promoted, so that quick consumption of the promotion budget of the content to be promoted is avoided, the bidding is adjusted through the content promotion budget and the promotion consumption calculation of the content to be promoted, the probability that the content to be promoted can bid successfully can be improved, whether the content to be promoted participates in bidding is controlled through the bidding probability, the promotion budget of the content to be promoted can be consumed is guaranteed through adjusting the bidding of the content to be promoted, the content to be promoted can be continuously exposed, and the promotion effect of the content to be promoted is improved.
The following will describe in detail. The following description of the embodiments is not intended to limit the preferred embodiments.
The present embodiment will be described from the viewpoint of a content promotion apparatus, which may be integrated in a computer device, which may be a server or a terminal, or other devices.
The embodiment of the application provides a content promotion method, as shown in fig. 2, which comprises the following specific procedures:
101. and predicting the content promotion frequency of the current promotion time and the promotion success rate of the content to be promoted at the current promotion time according to the historical promotion data.
The current promotion time may be a current period of time (1 minute, 30 minutes, or 1 hour, etc.), for example, the current time is ten in the morning, and then the current promotion time may be one hour from ten in the morning to 11 in the morning.
The historical promotion data may be promotion data of a period of time in which the current promotion time passes, and the promotion data may include content promotion frequency, promotion content bidding frequency, promotion success rate, bidding probability, bidding, and other data of the content to be promoted in the period of time in which the current promotion time passes.
The content promotion frequency may include the number of times content promotion is available in the past period of time, and may also include the number of times content promotion is available per unit time in the past period of time.
The frequency of popularization bidding may include the number of popularization contents participating in the popularization bidding when content popularization is available.
The promotion success rate of the content to be promoted can comprise the probability that the content to be promoted is displayed on the obtained webpage, and the promotion success rate can be the ratio of the number of times of displaying on the webpage to the promotion bidding frequency.
The bid probability may comprise a probability that the content to be promoted participates in the advertisement bid, and the bid probability may be a ratio between a promoting bid frequency and a content promoting frequency.
For example, in the past hour, the web page in which the promotion content is delivered has 1000 accesses, and the promotion content can be displayed through the web page, that is, the content promotion frequency is 1000, and if 100 promotion contents participate in promotion bidding, the promotion bidding frequency is 100. The number of times of displaying the content to be promoted on the webpage is 10, the promotion success rate of the content to be promoted is 60/100=0.6, namely 60%, and the bidding probability is 100/1000=0.1, namely 10%.
For example, the average content promotion frequency may be calculated according to the content promotion frequency corresponding to the historical promotion time with the same time length as the current promotion time in the historical promotion data, the average content promotion frequency is used as the content promotion time of the current promotion time, the average promotion success rate is calculated according to the promotion success rate corresponding to the content to be promoted in the historical promotion time, and the average promotion success rate is used as the promotion success rate of the content to be recommended in the current promotion time. For example, the current promotion time is 16:00-17:00, the historical promotion data comprise content promotion frequency and promotion success rate corresponding to each hour in the past 24 hours, and average content promotion frequency and average promotion success rate are calculated according to the content promotion frequency and promotion success rate corresponding to each hour in the past 24 hours respectively to obtain the content promotion frequency of the current promotion time and the promotion success rate of the content to be recommended in the current promotion time.
Optionally, the average content promotion frequency and the average promotion success rate can be calculated according to the content promotion frequency and the promotion success rate of the historical promotion time in the same time period as the current promotion time in the historical promotion data, so as to obtain the content promotion frequency of the current promotion time, and the promotion success rate of the content to be recommended in the current promotion time. For example, the current promotion time is 16:00-17:00, content promotion frequency and promotion success rate corresponding to past 16:00-17:00 are included according to historical promotion data, average content promotion frequency and average promotion success rate are calculated according to the content promotion frequency and promotion success rate corresponding to past 16:00-17:00, and content promotion frequency of the current promotion time and promotion success rate of the content to be recommended in the current promotion time are obtained.
Optionally, the content promotion frequency of the current promotion time and the promotion success rate of the content to be recommended in the current promotion time can be predicted based on the historical promotion data through the neural network.
Optionally, curve fitting may be performed according to historical promotion data, and the content promotion frequency of the current promotion time and the promotion success rate of the content to be recommended at the current promotion time are determined according to the obtained fitting curve, that is, in an embodiment, the historical promotion data includes promotion data of a plurality of historical promotion times, and the step of predicting the content promotion frequency of the current promotion time according to the historical promotion data and the promotion success rate of the content to be promoted at the current promotion time may specifically include:
Performing curve fitting according to popularization data of a plurality of historical popularization times in the historical popularization data to obtain a popularization frequency fitting curve and a success rate curve;
predicting content promotion frequency of the content to be promoted at the current promotion time based on the promotion frequency fitting curve;
and predicting the popularization success rate of the content to be promoted at the current popularization time based on the success rate curve.
Wherein, the historical promotion time can be a time period with the same time length as the current promotion time.
The promotion frequency fitting curve can represent the relationship between the content promotion frequency and the promotion time, and the promotion success rate can represent the relationship between the promotion success rate of the content to be promoted and the time.
For example, curve fitting is specifically performed on content promotion frequencies of a plurality of historical promotion times in the historical promotion data and promotion success rates of the content to be promoted, so that a promotion frequency fitting curve and a success rate curve are obtained respectively, and the content promotion frequency of the current promotion time and the promotion success rate of the content to be promoted are predicted based on the promotion frequency fitting curve and the success rate curve.
102. And calculating bidding probabilities of the content to be promoted participating in content promotion bidding at the current promotion time according to the historical promotion data, the content promotion frequency and the promotion success rate.
For example, a first ratio between the content promotion frequency and the historical content promotion frequency in the historical promotion data is calculated, a second ratio between the promotion success rate and the historical promotion success rate in the historical promotion data is calculated, a probability ratio of the bidding probability of the content to be promoted at the current promotion time to the historical bidding probability in the historical promotion data is determined according to an average ratio of the first ratio and the second ratio, and the bidding probability of the content to be promoted participating in the content promotion at the current promotion time is calculated based on the probability ratio and the historical bidding probability.
Because whether the content to be promoted participates in the promotion bid influences the promotion consumption of the content to be promoted, the promotion consumption is the cost of content promotion expense of the content to be promoted, if the cost is calculated by using exposure, the more the number of times of exposure (exposure is that the content to be promoted is displayed) of the content to be promoted is, the higher the promotion consumption is; if the conversion amount is used for charging, under the normal condition, the more the exposure times of the content to be promoted are, the higher the conversion amount is correspondingly, the more the exposure times of the content to be promoted are, the higher the promotion consumption of the content to be promoted is, and therefore, the promotion consumption of the content to be promoted is proportional to the exposure amount of the content to be promoted.
According to the popularization consumption of the content to be promoted, which is proportional to the exposure of the content to be promoted, the following relation can be obtained:
s t ∝req t ×pr t ×win t (1)
s t-1 ∝req t-1 ×pr t-1 ×win t-1 (2)
according to the formula (1) and the formula (2), a bid probability calculation formula of the content to be promoted at the current promotion time can be obtained:
wherein s is t Is the popularization consumption of the current popularization time, b t Is the average popularization consumption (the more the residual popularization budget is, the average popularization consumption and the popularization consumption are) of the current popularization time, and imp t To expose the content to be promoted at the current promotion time, req t To promote frequency of content at current promotion time, bid t To participate in the quantity of popularization contents of popularization bid at the current popularization time, pr t In order to bid probability, win of content to be promoted at current promotion time t For the bid success rate of the content to be promoted, B is the total promotion budget of the time period, T is the number of promotion times contained in the time period, for example, the time period is one day, the promotion time is a time period of 1 hour, then T is 24, and T-1 is the historical promotion time of the past of the time to be promoted.
Therefore, in an embodiment, step 102 "calculating, according to the historical promotion data, the content promotion frequency and the promotion success rate, a bid probability that the content to be promoted participates in content promotion bidding at the current promotion time" may specifically include:
Acquiring average popularization consumption of the content to be promoted in the current popularization time;
calculating a probability ratio between the current popularization time and the historical bidding probability based on the historical popularization data, the average popularization consumption, the popularization success rate and the content popularization frequency;
and calculating the bidding probability of the content to be promoted to participate in the content promotion bidding at the current promotion time based on the probability ratio and the historical bidding probability.
The specific process is described with reference to the above related content, and will not be described herein.
The bidding probability of the content to be promoted determines whether the content to be promoted participates in bidding or not, whileWhether the content to be promoted participates in bidding affects the promotion consumption and conversion Cost (CPA) of the content to be promoted, which may also be referred to as Cost Per Action, cpa=s t The conversion may include forming a transaction, obtaining a registered user, clicking on the promotion content, etc., the definition of the conversion may be set according to a specific application scenario, the excessive promotion consumption of the promotion content may result in excessively fast promotion budget consumption, the insufficient promotion budget left for subsequent promotion, and the insufficient promotion consumption of the promotion content may result in failure in bidding of the promotion content to be exposed, which is unfavorable for continuous exposure of the promotion content, so in an embodiment, a consumption range may be set, and the bidding probability of the promotion content to be adjusted within the consumption range so as to minimize CPA of the promotion content, i.e. "step 102" calculate the bidding probability of the promotion content to participate in content promotion bidding at the current promotion time according to historical promotion data, content promotion frequency and promotion success rate ", may specifically include:
a21, calculating initial bid probabilities of contents to be promoted participating in content promotion bidding at the current promotion time according to historical promotion data, content promotion frequency and promotion success rate;
a22, determining the popularization consumption range of the content to be promoted in the current popularization time according to a preset dynamic adjustment strategy;
a23, adjusting the initial bidding probability based on the popularization consumption range to obtain the bidding probability, wherein the bidding probability enables the conversion cost of the content to be promoted to meet the preset condition.
For example, the initial bid probability of the content to be promoted participating in the content promotion bid at the previous promotion time may be calculated according to the historical promotion data, the content promotion frequency and the promotion success rate, and the specific process may refer to the content description about calculating the bid probability in the step 102.
From equation (1), equation (1-2) can be derived, k being the scaling factor.
s t ∝req t ×pr t ×win t (1)
s t ＝k×req t ×pr t ×win t (1-2)
The initial popularization consumption s which can be calculated according to the initial bidding probability by using the formula (1-2) 0 The preset dynamic adjustment strategy may include an adjustable range of promotional consumption, e.g., the preset dynamic adjustment strategy includes an up-regulation range of promotional consumption: 5, and down-regulation range: 5, then, the popularization consumption range (s 0 -5,s 0 +5)。
The conversion times of the current popularization time can be determined by curve fitting according to the exposure and conversion times of the historical popularization time, can be determined according to the historical popularization time, the exposure and the makeup times of the historical popularization time, can be predicted through a neural network, and the like, and is not limited.
And in the content of the popularization consumption range, the initial bidding probability is adjusted, so that the popularization consumption is adjusted, and when the conversion cost of the content to be promoted reaches the minimum, the bidding probability is obtained.
Besides the preset adjustable range of the promotion consumption, the adjustable range of the promotion consumption can be determined according to the promotion budget of the content to be promoted, and the promotion consumption can be adjusted based on the promotion budget to more effectively ensure that the promotion budget of the content to be promoted is uniformly consumed, that is, in an embodiment, the step a22 "determines the promotion consumption range of the content to be promoted at the current promotion time according to the preset dynamic adjustment strategy" specifically may include:
a221, calculating a first consumption range of the content to be promoted in the current promotion time according to the total promotion budget of the content to be promoted and a first preset threshold value;
a222, calculating a second consumption range of the content to be promoted in the current promotion time according to the current promotion budget and a second preset threshold value;
a223, calculating a third consumption range of the content to be promoted in the current promotion time according to thousands of times of display inflow data of the content to be promoted and preset thousands of people cost;
a224, determining a popularization consumption range based on the first consumption range, the second consumption range and the third consumption range.
The total promotion budget can be a budget in one promotion period, the current promotion budget is a budget corresponding to the current promotion time, for example, the total promotion budget is a promotion budget of one day, and the current promotion budget can be a promotion budget of 16:00-17:00.
Wherein the thousand display inflow data (effective cost per mille, eCPM) may represent the total inflow of economic benefits available per thousand displays, which may also be referred to as thousands of display revenues.
The preset thousand-person cost can be preset thousand-person Cost (CPM) which refers to the cost required by the promotion to be heard or seen respectively for each thousand persons on average in the process of releasing the content to be promoted, and in the advertisement releasing scene, the thousand-person display income is the income obtained by displaying one thousand times on the website, and the thousand-person cost is the cost paid by an advertiser for releasing the advertisement to one thousand persons.
The first consumption range is calculated according to the following formula (3), the second consumption range is calculated according to the formula (4), and the third consumption range is calculated according to the formula (5). Wherein s is m For promotion consumption, B is the total promotion budget, ε is a first preset threshold, s t B, as popularization consumption of current popularization time t Is ideal popularization consumption of the current popularization time delta t For the second preset threshold, max (CPM) is the maximum value of preset thousand person costs.
|s t -b t |≤δ t (4)
eCPM≤max(CPM) (5)
103. If the bid probability meets the preset condition, calculating the current bid based on the content promotion budget and promotion consumption of the content to be promoted.
The content promotion budget may be an overall promotion budget of the content to be promoted, and the promotion consumption may be a cost spent in content promotion of the content to be promoted.
Specifically, if the bid probability satisfies a preset condition, for example, is greater than a preset threshold or satisfies a preset range, the remaining popularization budget k is calculated according to the content popularization budget and the popularization consumption t 。
The initial bid of the content to be promoted at the current promotion time is obtained, wherein the initial bid can be a preset bid, and the current bid is calculated according to the following formula.
b a (t)＝b 0 (t)exp(k t )
Wherein b 0 (t) initial bid, b a (t) is the current bid.
In one embodiment, the step of calculating the current bid based on the content promotion budget and promotion consumption of the content to be promoted may specifically include:
acquiring an initial bid of the content to be promoted at the current promotion time;
calculating bid adjustment parameters of the content to be promoted according to content promotion budget and promotion consumption of the content to be promoted;
and adjusting the initial bid of the content to be promoted at the current moment based on the bid adjustment parameter to obtain the current bid.
Wherein the initial bid may be a preset bid.
For example, the residual budget e of the current promotion time can be calculated according to the following formula (6) t After calculating according to formula (7) to obtain the bid adjustment parametersAt the initial bid b of the content to be promoted at the current moment based on the formula (8) 0 (t) adjusting to obtain the current bid b a (t)。
Wherein lambda is P 、λ I And lambda D Are all preset parameters.
104. And at the current popularization time, carrying out content popularization bidding on the content to be promoted by using the current bid.
For example, the content promotion bidding is performed with the current bid at the current promotion time.
If the content to be promoted is successfully bid, the content to be promoted can be displayed on the client, so in an embodiment, the content promotion method provided by the application specifically further comprises the following steps:
If the current bid meets the preset bidding condition, the content to be promoted is successful based on the current bidding;
and sending the content to be promoted to the promotion client so that the promotion client displays the content to be promoted.
For example, if the current bid of the content to be promoted is the highest bid of the content to be promoted, the content to be promoted is successfully bid, or if the current bid of the content to be promoted is the first 90% of the content to be promoted, the content to be promoted is successfully bid. And sending the content to be promoted, which is successfully bid, to the client, so that the client can display the content to be promoted.
As can be seen from the above, the embodiment of the application predicts the content promotion frequency of the current promotion time and the promotion success rate of the content to be promoted in the current promotion time according to the historical promotion data; calculating bidding probabilities of contents to be promoted participating in content promotion bidding at the current promotion time according to historical promotion data, content promotion frequency and promotion success rate; if the bidding probability meets the preset condition, calculating the current bid based on the content promotion budget and promotion consumption of the content to be promoted; and at the current popularization time, carrying out content popularization bidding on the content to be promoted by using the current bid.
According to the scheme, whether the content to be promoted participates in bidding is determined through predicting the bidding probability of the content to be promoted, so that quick consumption of the promotion budget of the content to be promoted is avoided, the bidding is adjusted through the content promotion budget and the promotion consumption calculation of the content to be promoted, the probability that the content to be promoted can bid successfully can be improved, whether the content to be promoted participates in bidding is controlled through the bidding probability, the promotion budget of the content to be promoted can be consumed is guaranteed through adjusting the bidding of the content to be promoted, the content to be promoted can be continuously exposed, and the promotion effect of the content to be promoted is improved.
On the basis of the above embodiments, examples will be described in further detail below.
The present embodiment will be described from the viewpoint of a content promotion apparatus, which may be integrated in a server in particular.
The embodiment of the application provides a content promotion method, as shown in fig. 3, which comprises the following specific procedures:
201. and the server acquires the content promotion budget of the content to be promoted.
For example, the content party of the content to be promoted can preset the total budget of the content to be promoted in one day, namely the content promotion budget, and can set initial bids of different time windows in one day, and set some thresholds, such as a first threshold, a second threshold and the like.
Alternatively, the server may split a day into 24 time windows, each of which may correspond to a promotion time. Optionally, the content promotion budget can be divided equally according to the number of the time windows, so as to obtain the promotion budget of each time window.
202. And the server predicts the content promotion frequency of the current promotion time and the promotion success rate of the content to be promoted according to the historical promotion data.
For example, specifically, the server may obtain a promotion frequency fitting curve and a success rate curve by performing curve fitting on the content promotion frequencies of a plurality of historical promotion times and promotion success rates of the content to be promoted in the historical promotion data, and predict the content promotion frequency of the current promotion time and the promotion success rate of the content to be promoted based on the promotion frequency fitting curve and the success rate curve.
203. The server calculates initial bid probability of the content to be promoted at the current promotion time based on the historical promotion data, the average promotion consumption, the promotion success rate and the content promotion frequency.
Because whether the content to be promoted participates in the promotion bid influences the promotion consumption of the content to be promoted, the promotion consumption is the cost of content promotion expense of the content to be promoted, if the cost is calculated by using exposure, the more the number of times of exposure (exposure is that the content to be promoted is displayed) of the content to be promoted is, the higher the promotion consumption is; if the conversion amount is used for charging, under the normal condition, the more the exposure times of the content to be promoted are, the higher the conversion amount is correspondingly, the more the exposure times of the content to be promoted are, the higher the promotion consumption of the content to be promoted is, and therefore, the promotion consumption of the content to be promoted is proportional to the exposure amount of the content to be promoted.
The server can obtain the following relation according to the popularization consumption of the content to be promoted in proportion to the exposure of the content to be promoted:
s t ∝req t ×pr t ×win t (1)
s t-1 ∝req t-1 ×pr t-1 ×win t-1 (2)
the server can obtain a bid probability calculation formula of the content to be promoted at the current promotion time according to the formula (1) and the formula (2):
wherein s is t Is the popularization consumption of the current popularization time, b t Is the average popularization consumption (the more the residual popularization budget is, the average popularization consumption and the popularization consumption are) of the current popularization time, and imp t To expose the content to be promoted at the current promotion time, req t To promote frequency of content at current promotion time, bid t To participate in the quantity of popularization contents of popularization bid at the current popularization time, pr t In order to bid probability, win of content to be promoted at current promotion time t For the bid success rate of the content to be promoted, B is the total promotion budget of the time period, T is the number of promotion times contained in the time period, for example, the time period is one day, the promotion time is a time period of 1 hour, then T is 24, and T-1 is the historical promotion time of the past of the time to be promoted.
204. And the server determines the popularization consumption range of the content to be promoted in the current popularization time according to a preset dynamic regulation strategy.
For example, the server may calculate the first consumption range according to the following formula (3), calculate the second consumption range according to the formula (4), and calculate the third consumption range according to the formula (5). Wherein s is m For promotion consumption, B is the total promotion budget, ε is a first preset threshold, s t B, as popularization consumption of current popularization time t Is ideal popularization consumption of the current popularization time delta t For the second preset threshold, max (CPM) is the maximum value of preset thousand person costs.
|s t -b t |≤δ t (4)
eCPM≤max(CPM) (5)
205. The server adjusts the initial bidding probability based on the popularization consumption range to obtain the bidding probability, and the bidding probability enables the conversion cost of the content to be promoted to meet the preset condition.
Since the bidding probability of the content to be promoted determines whether the content to be promoted participates in bidding, and whether the content to be promoted participates in bidding affects the promotion consumption and conversion Cost (CPA) of the content to be promoted, the conversion Cost may also be referred to as Cost Per Action, cpa=s t The conversion times can be formed by forming a transaction, obtaining a registered user, clicking on promotion content, and the like, and the definition of the conversion can be set according to specific application scenes.
The excessive consumption of the content to be promoted can cause the excessive consumption of the promotion budget, the content to be promoted does not have enough promotion budget remained for subsequent promotion, and the excessive consumption of the content to be promoted can cause the failure of bidding of the content to be promoted to be exposed, which is unfavorable for the continuous exposure of the content to be promoted.
Therefore, the bidding probability of the content to be promoted may be adjusted within the consumption range determined in step 204, so that the CPA of the content to be promoted is minimized, and when the conversion cost of the content to be promoted is minimized, the bidding probability is obtained.
206. If the bid probability meets the preset condition, the server calculates bid adjustment parameters of the content to be promoted according to the content promotion budget and promotion consumption of the content to be promoted.
For example, the server may calculate the residual budget e of the current promotion time according to the following formula (6) t After calculating according to formula (7) to obtain the bid adjustment parameters
Wherein lambda is P 、λ I And lambda D Are all preset parameters.
207. And the server adjusts the initial bid of the content to be promoted at the current moment based on the bid adjustment parameter to obtain the current bid.
For example, the server can specifically bid b for the content to be promoted at the current moment based on the formula (8) 0 (t) adjusting to obtain the current bid b a (t)。
208. And the server bids the content to be promoted with the current bid at the current promotion time.
For example, the server may bid for content promotion with the current bid for the content to be promoted at the current promotion time.
From the above, the server in the embodiment of the application obtains the content promotion budget of the content to be promoted; predicting content promotion frequency of current promotion time according to historical promotion data, and promoting success rate of content to be promoted; calculating initial bid probability of the content to be promoted at the current promotion time based on historical promotion data, average promotion consumption, promotion success rate and content promotion frequency; determining the popularization consumption range of the content to be promoted in the current popularization time according to a preset dynamic regulation strategy; adjusting the initial bidding probability based on the popularization consumption range to obtain bidding probability, wherein the bidding probability enables the conversion cost of the content to be promoted to meet the preset condition; if the bidding probability meets the preset condition, the server calculates bidding adjustment parameters of the content to be promoted according to the content promotion budget and promotion consumption of the content to be promoted; adjusting the initial bid of the content to be promoted at the current moment based on the bid adjustment parameter to obtain the current bid; and bidding the content to be promoted with the current bid at the current promotion time.
According to the scheme, whether the content to be promoted participates in bidding is determined through predicting the bidding probability of the content to be promoted, so that quick consumption of the promotion budget of the content to be promoted is avoided, the probability that the content to be promoted can bid successfully is improved through adjusting the bidding probability, whether the content to be promoted participates in bidding is controlled through the bidding probability, the promotion budget of the content to be promoted can be consumed uniformly through adjusting the bidding of the content to be promoted, continuous exposure of the content to be promoted can be achieved, and the promotion effect of the content to be promoted is improved.
In order to facilitate better implementation of the content promotion method provided by the embodiment of the application, in an embodiment, a content promotion device is also provided. The meaning of the nouns is the same as that in the popularization method, and specific implementation details can be referred to in the description of the method embodiment.
The content promotion device may be integrated in a computer device, as shown in fig. 4, and the content promotion device may include: the prediction unit 301, the first calculation unit 302, the second calculation unit 303, and the bidding unit 304 are specifically as follows:
(1) Prediction unit 301: the content promotion frequency and the promotion success rate of the content to be promoted at the current promotion time are used for predicting the content promotion frequency at the current promotion time according to the historical promotion data.
In an embodiment, the historical promotion data includes promotion data of a plurality of historical promotion times, and the prediction unit 301 includes a curve fitting subunit, a content promotion frequency prediction subunit, and a promotion success rate prediction subunit, specifically:
curve fitting subunit: the method comprises the steps of performing curve fitting according to popularization data of a plurality of historical popularization times in historical popularization data to obtain a popularization frequency fitting curve and a success rate curve;
content promotion frequency prediction subunit: the content promotion frequency is used for predicting the content to be promoted at the current promotion time based on the promotion frequency fitting curve;
Popularization success rate prediction subunit: the method is used for predicting the popularization success rate of the content to be promoted at the current popularization time based on the success rate curve.
(2) The first calculation unit 302: the method is used for calculating bidding probabilities that contents to be promoted participate in content promotion bidding at the current promotion time according to historical promotion data, content promotion frequency and promotion success rate.
In an embodiment, the first computing unit 302 comprises a probability computing subunit, a range determining subunit and a probability adjusting subunit, in particular:
probability calculation subunit: the method comprises the steps of calculating initial bid probabilities of contents to be promoted participating in content promotion bidding at current promotion time according to historical promotion data, content promotion frequency and promotion success rate;
range determination subunit: the method comprises the steps of determining a popularization consumption range of content to be promoted in current popularization time according to a preset dynamic regulation strategy;
probability adjustment subunit: the method is used for adjusting the initial bidding probability based on the popularization consumption range to obtain the bidding probability, and the bidding probability enables the conversion cost of the content to be promoted to meet the preset condition.
In an embodiment, the range determination subunit includes a first range determination module, a second range determination module, a third range determination module, and a promotional consumption range determination module, in particular:
A first range determination module: the method comprises the steps of calculating a first consumption range of the content to be promoted in the current promotion time according to the total promotion budget of the content to be promoted and a first preset threshold value;
a second range determination module: the method comprises the steps of calculating a second consumption range of content to be promoted in current promotion time according to current promotion budget and a second preset threshold;
a third range determination module: the method comprises the steps of calculating a third consumption range of the content to be promoted in the current promotion time according to thousands of times of display inflow data of the content to be promoted and preset thousands of people cost;
popularization consumption range determining module: for determining a promotional consumption range based on the first consumption range, the second consumption range, and the third consumption range.
In an embodiment, the historical promotional data comprises a historical bid probability, and the first computing unit 302 comprises a consumption computing subunit, a probability ratio subunit, and a probability computing subunit, specifically:
consumption calculation subunit: the method comprises the steps of obtaining average popularization consumption of content to be promoted in current popularization time;
probability ratio subunit: the method is used for calculating the probability ratio between the current popularization time and the historical bidding probability based on the historical popularization data, the average popularization consumption, the popularization success rate and the content popularization frequency;
Probability calculation subunit: the method is used for calculating the initial bidding probability of the content to be promoted to participate in the content promotion bid at the current promotion time based on the probability ratio and the historical bidding probability.
(3) The second calculation unit 303: and if the bidding probability meets the preset condition, calculating the current bid based on the promotion budget and the residual promotion budget of the content to be promoted.
In an embodiment, the second calculation unit 303 comprises an acquisition subunit, a parameter calculation subunit and a bid adjustment subunit, in particular:
an acquisition subunit: the method comprises the steps of obtaining initial bid of content to be promoted at current promotion time;
parameter calculation subunit: the bid adjustment parameters of the content to be promoted are calculated according to the content promotion budget and promotion consumption of the content to be promoted;
bid adjustment subunit: and the bid adjustment parameter is used for adjusting the initial bid of the content to be promoted at the current moment based on the bid adjustment parameter to obtain the current bid.
(4) Bidding unit 304: and the method is used for bidding the content promotion of the content to be promoted with the current bid at the current promotion time.
In an embodiment, the content promotion apparatus further includes a bid result determination unit and a content transmission unit, specifically:
bid result determination unit: if the current bid meets the preset bidding condition, determining that the content to be promoted is successful based on the current bidding;
Content transmitting unit: and the promotion client is used for sending the content to be promoted to the promotion client so that the promotion client displays the content to be promoted.
As can be seen from the above, the content promotion device according to the embodiment of the present application predicts the content promotion frequency of the current promotion time and the promotion success rate of the content to be promoted at the current promotion time according to the historical promotion data by the prediction unit 301; calculating bidding probabilities of contents to be promoted participating in content promotion bidding at the current promotion time by a first calculation unit 302 according to historical promotion data, content promotion frequency and promotion success rate; if the bid probability meets the preset condition, calculating a current bid by the second calculation unit 303 based on the content promotion budget and promotion consumption of the content to be promoted; finally, the content to be promoted is subjected to content promotion bidding with the current bid at the current promotion time through the bidding unit 304.
According to the scheme, whether the content to be promoted participates in bidding is determined through predicting the bidding probability of the content to be promoted, so that quick consumption of the promotion budget of the content to be promoted is avoided, the bidding is adjusted through the content promotion budget and the promotion consumption calculation of the content to be promoted, the probability that the content to be promoted can bid successfully can be improved, whether the content to be promoted participates in bidding is controlled through the bidding probability, the promotion budget of the content to be promoted can be consumed is guaranteed through adjusting the bidding of the content to be promoted, the content to be promoted can be continuously exposed, and the promotion effect of the content to be promoted is improved.
The embodiment of the application also provides a computer device, which may be a terminal or a server, as shown in fig. 5, and shows a schematic structural diagram of the computer device according to the embodiment of the application, specifically:
the computer device may include one or more processors 1001 of a processing core, one or more memories 1002 of a computer readable storage medium, a power supply 1003, and an input unit 1004, among other components. Those skilled in the art will appreciate that the computer device structure shown in FIG. 5 is not limiting of the computer device and may include more or fewer components than shown, or may be combined with certain components, or a different arrangement of components. Wherein:
the processor 1001 is a control center of the computer device, connects respective portions of the entire computer device using various interfaces and lines, and performs various functions of the computer device and processes data by running or executing software programs and/or modules stored in the memory 1002 and calling data stored in the memory 1002, thereby performing overall monitoring of the computer device. Optionally, the processor 1001 may include one or more processing cores; preferably, the processor 1001 may integrate an application processor and a modem processor, wherein the application processor mainly processes an operating system, a user interface, a computer program, and the like, and the modem processor mainly processes wireless communication. It will be appreciated that the modem processor described above may not be integrated into the processor 1001.
The memory 1002 may be used to store software programs and modules, and the processor 1001 executes various functional applications and data processing by executing the software programs and modules stored in the memory 1002. The memory 1002 may mainly include a stored program area that may store an operating system, computer programs required for at least one function (such as a sound playing function, an image playing function, etc.), and a stored data area; the storage data area may store data created according to the use of the computer device, etc. In addition, memory 1002 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, the memory 1002 may also include a memory controller to provide the processor 1001 with access to the memory 1002.
The computer device also includes a power supply 1003 for powering the various components, preferably, the power supply 1003 is logically connected to the processor 1001 by a power management system, such that charge, discharge, and power consumption management functions are performed by the power management system. The power supply 1003 may also include one or more of any of a direct current or alternating current power supply, a recharging system, a power failure detection circuit, a power converter or inverter, a power status indicator, and the like.
The computer device may also include an input unit 1004, which input unit 1004 may be used to receive input numeric or character information and to generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control.
Although not shown, the computer device may further include a display unit or the like, which is not described herein. In particular, in this embodiment, the processor 1001 in the computer device loads executable files corresponding to the processes of one or more computer programs into the memory 1002 according to the following instructions, and the processor 1001 executes the computer programs stored in the memory 1002, so as to implement various functions, as follows:
predicting content promotion frequency of the current promotion time according to the historical promotion data, and promoting success rate of the content to be promoted in the current promotion time;
calculating bidding probabilities of contents to be promoted participating in content promotion bidding at the current promotion time according to historical promotion data, content promotion frequency and promotion success rate;
if the bidding probability meets the preset condition, calculating the current bid based on the content promotion budget and promotion consumption of the content to be promoted;
And at the current popularization time, carrying out content popularization bidding on the content to be promoted by using the current bid.
The specific implementation of each operation may be referred to the previous embodiments, and will not be described herein.
As can be seen from the above, the computer device according to the embodiment of the present application can predict the content promotion frequency of the current promotion time and the promotion success rate of the content to be promoted at the current promotion time according to the historical promotion data; calculating bidding probabilities of contents to be promoted participating in content promotion bidding at the current promotion time according to historical promotion data, content promotion frequency and promotion success rate; if the bidding probability meets the preset condition, calculating the current bid based on the content promotion budget and promotion consumption of the content to be promoted; and at the current popularization time, carrying out content popularization bidding on the content to be promoted by using the current bid.
According to the scheme, whether the content to be promoted participates in bidding is determined through predicting the bidding probability of the content to be promoted, so that quick consumption of the promotion budget of the content to be promoted is avoided, the bidding is adjusted through the content promotion budget and the promotion consumption calculation of the content to be promoted, the probability that the content to be promoted can bid successfully can be improved, whether the content to be promoted participates in bidding is controlled through the bidding probability, the promotion budget of the content to be promoted can be consumed is guaranteed through adjusting the bidding of the content to be promoted, the content to be promoted can be continuously exposed, and the promotion effect of the content to be promoted is improved.
According to one aspect of the present application, there is provided a computer program product comprising a computer program comprising computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions to cause the computer device to perform the methods provided in the various alternative implementations of the above embodiments.
It will be appreciated by those of ordinary skill in the art that all or part of the steps of the various methods of the above embodiments may be performed by a computer program, or by computer program control related hardware, which may be stored in a computer readable storage medium and loaded and executed by a processor.
To this end, an embodiment of the present application provides a computer-readable storage medium in which a computer program is stored, the computer program being capable of being loaded by a processor to perform any one of the content promotion methods provided by the embodiment of the present application.
The specific implementation of each operation above may be referred to the previous embodiments, and will not be described herein.
Wherein the computer-readable storage medium may comprise: read Only Memory (ROM), random access Memory (RAM, random Access Memory), magnetic or optical disk, and the like.
Because the computer program stored in the computer readable storage medium can execute any content promotion method provided by the embodiment of the present application, the beneficial effects that any content promotion method provided by the embodiment of the present application can be achieved, and detailed descriptions of the foregoing embodiments are omitted herein.
The foregoing has described in detail the methods, apparatus, computer devices and computer readable storage medium for content promotion provided by the embodiments of the present application, and specific examples have been applied to illustrate the principles and embodiments of the present application, and the description of the foregoing embodiments is only for aiding in the understanding of the methods and core ideas of the present application; meanwhile, as those skilled in the art will have variations in the specific embodiments and application scope in light of the ideas of the present application, the present description should not be construed as limiting the present application.

Claims (11)

1. A content promotion method, comprising:
Predicting content promotion frequency of current promotion time according to historical promotion data, and promoting success rate of content to be promoted in the current promotion time;
calculating bidding probabilities of the content to be promoted participating in content promotion bidding at the current promotion time according to the historical promotion data, the content promotion frequency and the promotion success rate;
if the bid probability meets the preset condition, calculating a current bid based on the popularization budget and the residual popularization budget of the content to be promoted;
and at the current promotion time, carrying out content promotion bidding on the content to be promoted by the current bid.
2. The method of claim 1, wherein the calculating the bid probability of the content to be promoted to participate in the content promotion bid at the current promotion time based on the historical promotion data, the content promotion frequency, and the promotion success rate comprises:
according to the historical popularization data, the content popularization frequency and the popularization success rate, calculating initial bidding probability that the content to be promoted participates in content popularization bidding at the current popularization time;
determining the popularization consumption range of the content to be promoted in the current popularization time according to a preset dynamic regulation strategy;
And adjusting the initial bidding probability based on the popularization consumption range to obtain the bidding probability, wherein the bidding probability enables the conversion cost of the content to be promoted to meet a preset condition.
3. The method according to claim 2, wherein the calculating the promotion consumption range of the content to be promoted at the current promotion time according to the preset dynamic adjustment policy includes:
calculating a first consumption range of the content to be promoted in the current promotion time according to the total promotion budget of the content to be promoted and a first preset threshold value;
calculating a second consumption range of the content to be promoted in the current promotion time according to the current promotion budget and a second preset threshold;
calculating a third consumption range of the content to be promoted in the current promotion time according to the thousands of times of display inflow data of the content to be promoted and preset thousands of people cost;
the promotional consumption range is determined based on the first consumption range, the second consumption range, and the third consumption range.
4. The method of claim 1, wherein the historical promotion data includes a historical bid probability, and wherein calculating the bid probability that the content to be promoted participates in content promotion bidding at the current promotion time based on the historical promotion data, the content promotion frequency, and the promotion success rate comprises:
Acquiring average popularization consumption of the content to be promoted in the current popularization time;
calculating a probability ratio between a current promotion time and the historical bid probability based on the historical promotion data, the average promotion consumption, the promotion success rate and the content promotion frequency;
and calculating the initial bid probability of the content to be promoted to participate in content promotion bidding at the current promotion time based on the probability ratio and the historical bid probability.
5. The method of claim 1, wherein the calculating the current bid based on the content promotion budget and promotion consumption of the content to be promoted comprises:
acquiring an initial bid of the content to be promoted at the current promotion time;
calculating bid adjustment parameters of the content to be promoted according to the content promotion budget and promotion consumption of the content to be promoted;
and adjusting the initial bid of the content to be promoted at the current moment based on the bid adjustment parameter to obtain the current bid.
6. The method of claim 1, wherein the historical promotion data comprises promotion data for a plurality of historical promotion times, wherein predicting content promotion frequency for a current promotion time and promotion success rate for content to be promoted at the current promotion time based on the historical promotion data comprises:
Performing curve fitting according to popularization data of a plurality of historical popularization times in the historical popularization data to obtain a popularization frequency fitting curve and a success rate curve;
predicting content promotion frequency of the content to be promoted at the current promotion time based on the promotion frequency fitting curve;
and predicting the popularization success rate of the content to be promoted at the current popularization time based on the success rate curve.
7. The method according to any one of claims 1-6, further comprising:
if the current bid meets a preset bidding condition, determining that the content to be promoted is successful based on the current bidding;
and sending the content to be promoted to a promotion client so that the promotion client displays the content to be promoted.
8. A content promotion apparatus, comprising:
the prediction unit is used for predicting content promotion frequency of the current promotion time and promotion success rate of the content to be promoted at the current promotion time according to the historical promotion data;
the first calculating unit is used for calculating bidding probabilities of the content to be promoted participating in content promotion bidding at the current promotion time according to the historical promotion data, the content promotion frequency and the promotion success rate;
The second calculating unit is used for calculating the current bid based on the promotion budget and the residual promotion budget of the content to be promoted if the bid probability meets the preset condition;
and the bidding unit is used for bidding the content to be promoted by the current bid at the current promotion time.
9. A computer device comprising a memory and a processor; the memory stores a computer program, and the processor is configured to execute the computer program in the memory to perform the content promotion method according to any one of claims 1 to 7.
10. A computer-readable storage medium storing a computer program, the computer program being loaded by a processor to perform the content promotion method of any one of claims 1 to 7.
11. A computer program product comprising a computer program, characterized in that the computer program, when executed by a processor, implements the content promotion method of any one of claims 1 to 7.
CN202210365056.1A 2022-04-07 2022-04-07 Content promotion method, content promotion device, computer equipment, storage medium and product Pending CN116934397A (en)

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